Dataset card: full best-practices pass (source attribution, licensing/PII, citation, mailroom refs; fix dead companion link)

README.md

@@ -1,9 +1,18 @@
 ---
 license: other
+license_name: research-only-enron-corpus
 task_categories:
 - text-classification
 language:
 - en
+language_creators:
+- found
+multilinguality:
+- monolingual
+annotations_creators:
+- machine-generated
+source_datasets:
+- extended
 tags:
 - legal
 - enron
@@ -36,12 +45,12 @@ configs:
 
 # Enron Correspondence Deduplicated (Enriched GT, Agent-Blind Default)
 
-The **deduplicated, ground-truth-enriched** companion to
-[`Lucius-Morningstar/enron-correspondence`](https://huggingface.co/datasets/Lucius-Morningstar/enron-correspondence):
-exact-duplicate bodies removed from the cleaned CMU Enron corpus (517,390
-rows in -> **247,523 unique-text rows out**, 269,867 duplicates dropped;
-first occurrence wins on maildir-path order; empty bodies never deduped against
-each other).
+The **deduplicated, ground-truth-enriched** Enron correspondence benchmark:
+exact-duplicate bodies removed from the cleaned CMU Enron corpus (**517,390
+rows in → 247,523 unique-text rows out**, 269,867 duplicates dropped; first
+occurrence wins on maildir-path order; empty bodies never deduped against
+each other). This dataset is the core evaluation corpus for the
+[LLM Mailroom](https://github.com/Exios66/llm-mailroom) agent-sorting stack.
 
 ## ⚠️ Two-config layout: agents get NO answers by default
 
@@ -80,20 +89,24 @@ JSON. The single-file 548 MB `blind/train.jsonl` crashed the Dataset Viewer's
 conversion worker (`JobManagerCrashedError`); serving parquet directly removes
 that conversion step entirely.
 
+A machine-readable build manifest (`manifest.txt`) records schema version,
+row counts, and the dedup/enrichment provenance chain.
+
 ## Ground-truth dimensions
 
 1. **doc_type / subclass** (`expected`, `expected_subclass`,
    `label_evidence`) — heuristic form taxonomy from the shared
-   [`correspondence_subclasses`](https://github.com/Exios66/Enron-Evaluation-Environment)
+   [`correspondence_subclasses`](https://github.com/Exios66/Enron-Evaluation-Environment/blob/main/scripts/correspondence_subclasses.py)
    labeler: attorney_demand, demand, email, letter, meeting_request, memo, notice, press_release.
 2. **content_topic** (`content_topic`, `topic_evidence`) — WHAT the message
    body is about: an 11-key priority-scored marker taxonomy
-   (`content_topics.py`): legal_contracts, regulatory, finance_earnings, energy_market, hr_personnel, it_systems, travel_logistics, marketing_clients, announcements, scheduling.
+   ([`content_topics.py`](https://github.com/Exios66/Enron-Evaluation-Environment/blob/main/scripts/content_topics.py)):
+   legal_contracts, regulatory, finance_earnings, energy_market, hr_personnel, it_systems, travel_logistics, marketing_clients, announcements, scheduling.
 3. **sentiment** (`sentiment_score` ∈ [-1, 1], `sentiment_label` ∈
    negative/neutral/positive, `sentiment_evidence`) — deterministic lexicon
    polarity over the subject + forwarded-tail-stripped body
-   (`sentiment_scorer.py`), negation/intensifier-aware, politeness-formula
-   controlled.
+   ([`sentiment_scorer.py`](https://github.com/Exios66/Enron-Evaluation-Environment/blob/main/scripts/sentiment_scorer.py)),
+   negation/intensifier-aware, politeness-formula controlled.
 
 All three dimensions are HEURISTIC ground truth (deterministic pure functions,
 human-reviewed via spot checks where noted) — not hand annotations. Honest
@@ -109,13 +122,96 @@ Per-row `split` follows the family rule `md5(filename) % 10 == 0 -> test`
 dedup/enrichment cannot change any surviving row's split. Coverage: train
 222,572 / test 24,951.
 
+## Source data & original download
+
+All content derives from the **CMU Enron Email Dataset** — Bryan Klimt and
+Yiming Yang, Carnegie Mellon University, 2004. Original public download
+source: **https://www.cs.cmu.edu/~enron/**
+
+- Roughly 500,000 messages from ~150 Enron employees, released by the Federal
+  Energy Regulatory Commission during the fraud investigation and cleaned and
+  published for research by CMU.
+- We ingest the cleaned `maildir` variant; each row preserves its provenance
+  in `metadata.source` (`cmu_enron_maildir`), `metadata.custodian`,
+  `metadata.folder`, and `metadata.message_id`.
+- The full-corpus export step (sha256-verified, 517,390 rows) was produced by
+  [`publish_enron_correspondence.py`](https://github.com/Exios66/llm-entity-extraction/blob/main/scripts/datasets/publish_enron_correspondence.py);
+  dedup uses `body_hash` from
+  [`scripts/dedupe.py`](https://github.com/Exios66/Enron-Evaluation-Environment/blob/main/scripts/dedupe.py)
+  in Enron-Evaluation-Environment.
+
+## Licensing and appropriate use
+
+- Released for **research use**, consistent with the original CMU Enron
+  release terms (recorded per-row in `metadata.license`: "Enron corpus —
+  released for research use"). Hub license badge: `research-only-enron-corpus`
+  (custom, `license: other`).
+- The corpus contains **real personally identifying information** (names,
+  addresses, phone numbers) of Enron employees and correspondents. Treat all
+  rows as sensitive research data: no redistribution of raw PII outside
+  research contexts, and no use in production or consumer-facing systems.
+- Label columns are deterministic heuristics (see honest-gaps notes above),
+  suitable as routing priors and weak supervision — not as gold human
+  annotation.
+- Provided as-is, with no warranty of any kind. Downstream users are
+  responsible for complying with the original CMU/FERC terms.
+
+## Related projects
+
+- [LLM Mailroom](https://github.com/Exios66/llm-mailroom) — the agentic
+  email-triage system this benchmark evaluates; the blind/ground-truth split
+  exists precisely so sorting agents can be scored without label leakage.
+- [Enron-Evaluation-Environment](https://github.com/Exios66/Enron-Evaluation-Environment) —
+  labelers (`correspondence_subclasses.py`, `content_topics.py`,
+  `sentiment_scorer.py`) and the dedup rule (`scripts/dedupe.py::body_hash`).
+- [llm-entity-extraction](https://github.com/Exios66/llm-entity-extraction) —
+  dataset publishing pipelines (`scripts/datasets/publish_enron_*.py`).
+- Companion Hub datasets from the same family:
+  [legalbench-full](https://huggingface.co/datasets/Lucius-Morningstar/legalbench-full),
+  [docclass-merged](https://huggingface.co/datasets/Lucius-Morningstar/docclass-merged),
+  [mailroom-cuad-contracts](https://huggingface.co/datasets/Lucius-Morningstar/mailroom-cuad-contracts),
+  [mailroom-cuad-contracts-full](https://huggingface.co/datasets/Lucius-Morningstar/mailroom-cuad-contracts-full).
+
+Note: an earlier companion repo `Lucius-Morningstar/enron-correspondence` (the
+pre-dedup full corpus) is no longer published on the Hub; reproduce it with
+`publish_enron_correspondence.py` instead.
+
+## Citation
+
+If you use this dataset, please cite both the dataset and the underlying
+corpus:
+
+```bibtex
+@misc{morningstar2026enroncorrespondencededup,
+  title        = {Enron Correspondence Deduplicated (Enriched GT, Agent-Blind Default)},
+  author       = {Lucius-Morningstar},
+  year         = {2026},
+  month        = {August},
+  howpublished = {\url{https://huggingface.co/datasets/Lucius-Morningstar/enron-correspondence-dedup}},
+}
+
+@inproceedings{klimt2004enron,
+  title     = {The Enron Corpus: A New Dataset for Email Classification Research},
+  author    = {Klimt, Bryan and Yang, Yiming},
+  booktitle = {European Conference on Machine Learning (ECML 2004)},
+  pages     = {217--226},
+  year      = {2004}
+}
+```
+
 ## Provenance
 
 Built by [`llm-entity-extraction`](https://github.com/Exios66/llm-entity-extraction)
 `scripts/datasets/publish_enron_correspondence_dedup.py` (KANBAN-079,
 2026-08-23T18:52:37+00:00) from the sha256-verified full-corpus export (LFS
-`0554a5973935…`). Labelers: Enron-Evaluation-Environment `scripts/`
-(`correspondence_subclasses.py`, `content_topics.py`,
-`sentiment_scorer.py`). Source: CMU Enron Email Dataset (cleaned maildir);
-dedup rule `scripts/dedupe.py::body_hash`. Research-use license — treat
-personally identifying content accordingly.
+`0554a5973935…`). Labelers and dedup rule: Enron-Evaluation-Environment
+`scripts/` (`correspondence_subclasses.py`, `content_topics.py`,
+`sentiment_scorer.py`, `dedupe.py`). Source: CMU Enron Email Dataset (cleaned
+maildir). Parquet shards added 2026-08-23 (same-day viewer fix, verified
+row-for-row against the JSONL originals).
+
+## Maintenance
+
+Issues and fixes: [llm-entity-extraction issues](https://github.com/Exios66/llm-entity-extraction/issues)
+or contact [@Lucius-Morningstar](https://huggingface.co/Lucius-Morningstar)
+on the Hub.